Transcriptional Regulation of Acute Phase Protein Genes
Notice bibliographique
Résumé
LPS/TLR4-dependent macrophage inflammatory responses are coordinated by combinations of transcription factorsMacrophages are important regulators of the inflammatory response, and sense bacterial products through Toll-like receptors (TLR).For example, TLR4 senses the presence of Gram negative bacterial lipopolysaccharide (LPS).LPS, in a complex with LPS-binding protein (LBP), is transferred by CD14 to a TLR4/MD-2 cell surface receptor.Ligand binding leads to MyD88 signaling through IRAK1/IRAK2/IRAK4 and TAK1 kinase activation, and subsequent activation of downstream signaling kinases, such as IKKs, MAPkinases ERK1/2, p38 and JNK, which affect NF-κB and AP-1 transcription factor activities.In addition, a TRIF-dependent pathway activates kinases such as TAK1 and TBK1 and IKK non-canonical IKKs, leading respectively to NF-κB and IRF3 activation (Kumar et al., 2011).As a result, TLR4 activation induces acute inflammation in macrophages, characterized by the expression of a series of genes, such as cytokines, chemokines and antibacterial peptides, among others.These genes are temporally regulated, with early expressed or primary response genes, and late expressed or secondary response genes.In contrast to primary www.intechopen.com Acute Phase Proteins -Regulation and Functions of Acute Phase Proteins 2response genes, secondary response genes need new protein synthesis to establish full expression patterns.This complex regulation depends on an array of transcription factors that may be divided in four classes (Medzhitov and Horng, 2009) (Table 1).The first two classes of transcription factors are ubiquitous stress sensors that respond to external stress signals.Class I includes constitutively expressed transcription factors, such as NF-κB and IRF3, activated by signaldependent post-translational modifications that affect their activation properties and nuclear localization.For example, cytoplasmic NF-κB is rapidly translocated to the nucleus after LPS stimulation, and is involved in the induction of primary genes.Other transcription factors of this class include latent nuclear AP-1 transcription factors, such as c-Jun phosphorylated rapidly after LPS stimulation.Class II transcription factors, including C/EBP and AP-1 transcription factor family members, need new protein synthesis for LPSdependent stimulation.In addition to inducing secondary late gene expression, these transcription factors play a role in determining waves of time-dependent levels of gene expression.In macrophages, CCAAT/enhancer-binding protein (C/EBP ) expression is increased late after LPS induction (see below).The two last classes comprise tissue-restricted and cell-lineage transcription factors.The third category includes the macrophage-differentiation transcription factors PU.1 and C/EBP .Transcription factors of this class establish inducible cell-specific responses to stress and inflammation, by generating macrophage-specific chromatin domain modifications.The fourth category includes metabolic sensors of the nuclear receptor family, such as peroxisome proliferator-activated receptors (PPARs) and liver X receptors (LXR), activated respectively by fatty acids and cholesterol metabolites (Glass and Saijo, 2010).These ligand-dependent transcription factors are anti-inflammatory and link metabolism and tissue inflammation.Recent findings have uncovered a general view of the various regulatory mechanisms establishing differential gene-specific patterns of primary and secondary gene expression after LPS stimulation in macrophages.These studies have determined the role of transcription factors, chromatin modifications and structure in gene regulation from transcription start sites and proximal promoter elements, or from enhancers, with microarray data generating genome-wide expression patterns, global chromatin immunoprecipitation experiments (ChIPon-ChIP), real-time PCR analysis and massively parallel sequencing.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».